Borderline personality disorder: is diagnosis offering service or stigma?
Bibliographic record
Abstract
Borderline personality disorder (BPD) is a common diagnosis I encountered while on my psychiatry rotation. The stigma surrounding the diagnosis and the negative attitudes of health care professionals towards these patients raised interesting questions regarding the approach to and benefit of formal diagnosis. Through reflection, two important learning points are proposed: be aware of the stigma towards BPD patients and approach each patient with an open mind and a professional attitude, and carefully examine the context of BPD symptoms before attributing a patient’s difficulties to a single diagnosis. RÉSUMÉ Le trouble de la personnalité limite (TPL) est un diagnostic commun que j’ai croisé au cours de mon stage en psychiatrie. La stigmati- sation entourant ce diagnostic et les attitudes négatives des professionnels de la santé face à ces patients soulèvent d’intéressantes questions quant à l’avantage d’établir un diagnostic officiel et l’approche à suivre pour y arriver. À la suite de réflexions, deux éléments importants à retenir sont suggérés : être conscient de la stigmatisation envers les patients avec le TPL et approcher chaque patient avec un esprit ouvert et une attitude professionnelle, et examiner attentivement le contexte entourant les symptômes du TPL avant d’attribuer les difficultés des patients à un seul diagnostic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".